Transcription of AN INTRODUCTION TO MULTIVARIATE STATISTICS
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AN INTRODUCTION TO MULTIVARIATE STATISTICS
An INTRODUCTION to MULTIVARIATE STATISTICS The term MULTIVARIATE STATISTICS is appropriately used to include all STATISTICS where there are more than two variables simultaneously analyzed. You are already familiar with bivariate STATISTICS such as the Pearson product moment correlation coefficient and the independent groups t-test. A one-way ANOVA with 3 or more treatment groups might also be considered a bivariate design, since there are two variables: one independent variable and one dependent variable. Statistically, one could consider the one-way ANOVA as either a bivariate curvilinear regression or as a multiple regression with the K level categorical independent variable dummy coded into K-1 dichotomous variables.
Rank-Data I have mentioned the assumption of normality common to “parametric” inferential statistics. Please note that ordinal data may be normally distributed and interval data may not, so scale of measurement is irrelevant. Both ordinal and interval data may be distributed in any way. There is no relationship between
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